Channel conditions in communication systems vary over time. Such variances occur in all communication systems, and may be marked particularly in systems in which subscriber stations are moving. Spectral efficiency is a very important aspect of all communication systems. Conservative algorithms for modulation and coding schemes (MCS) may lead to lower throughput rates. Aggressive algorithms for MCS may lead to higher packet loss and retransmissions. Although the bits-per-Hz efficiency is higher with aggressive modulation algorithms, retransmissions may indirectly lower the overall spectral efficiency of the system. Best link adaptation algorithms define optimal MCS and optimal antenna methods to be used for data transmission for each individual subscriber, depending upon channel conditions between the Base station and the subscriber station.
Various link adaptation algorithms are available today, based on the received signal strength (RSSI) and Signal to Noise ratio (SNR). A transmitter must rely on channel conditions (such as RSSI/SNR) reported by the receiver, but channel conditions vary dramatically in any communication system, and particularly when a subscriber station is moving. Channel measurement reports from the receiver are periodic. In changing environments, particularly but not solely in mobile environments, when channel is fading, a report received from the receiver may not be appropriate by the time MCS is estimated and the transmission takes place. If the channel conditions have improved, then the selected MCS may result in lower throughput and spectral efficiency until the next report is received. If the channel conditions have worsened, then the selected MCS may result in lot of transmission errors and retransmissions. Increase in transmission errors and retransmissions may, at the higher layers, be realized as high packet latency and a lower throughput of the system.
Another issue with current adaption algorithms is that the receiver estimates the channel conditions based on the size of the received data burst. Channel estimated on a smaller burst may not be valid for a larger burst, since the RSSI/SNR measurement is usually stronger on smaller burst. This is especially true in uplink transmissions received from the subscriber station, since uplink transmissions are typically constrained by available power limitations. This is true even in case of an adaptive white Gaussian noise (AWGN) channel. Sometimes in dense urban environments, channel conditions estimated by the receiver may be wrong, due to high multipath fading.
Another issue with current adaptation algorithms is often seen with TCP-type of flow in communication systems. If the rate chosen is higher, this may cause initial packet loss to TCP stream. If the problem is sufficiently severe, the TCP may not even start.